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docs/en/faq/index.md
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# Frequently Asked Questions # Frequently Asked Questions
If your question is not listed, you can also use [DeepWiki](https://deepwiki.com/opendatalab/MinerU) to communicate with the AI assistant, which can solve most common problems. If your question is not listed, try using [DeepWiki](https://deepwiki.com/opendatalab/MinerU)'s AI assistant for common issues.
If you still cannot resolve the issue, you can join the community through [Discord](https://discord.gg/Tdedn9GTXq) or [WeChat](http://mineru.space/s/V85Yl) to communicate with other users and developers. For unresolved problems, join our [Discord](https://discord.gg/Tdedn9GTXq) or [WeChat](http://mineru.space/s/V85Yl) community for support.
??? question "Encountered the error `ImportError: libGL.so.1: cannot open shared object file: No such file or directory` in Ubuntu 22.04 on WSL2" ??? question "Encountered the error `ImportError: libGL.so.1: cannot open shared object file: No such file or directory` in Ubuntu 22.04 on WSL2"
......
docs/en/quick_start/index.md
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...@@ -93,4 +93,9 @@ You can get the [Docker Deployment Instructions](./docker_deployment.md) in the ...@@ -93,4 +93,9 @@ You can get the [Docker Deployment Instructions](./docker_deployment.md) in the
### Using MinerU ### Using MinerU
The simplest command line invocation is:
```bash
mineru -p <input_path> -o <output_path>
```
You can use MinerU for PDF parsing through various methods such as command line, API, and WebUI. For detailed instructions, please refer to the [Usage Guide](../usage/index.md). You can use MinerU for PDF parsing through various methods such as command line, API, and WebUI. For detailed instructions, please refer to the [Usage Guide](../usage/index.md).
\ No newline at end of file
docs/en/usage/index.md
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# Using MinerU # Usage Guide
## Quick Model Source Configuration This section provides comprehensive usage instructions for the project. We will help you progressively master the project's usage from basic to advanced through the following sections:
MinerU uses `huggingface` as the default model source. If users cannot access `huggingface` due to network restrictions, they can conveniently switch the model source to `modelscope` through environment variables:
```bash
export MINERU_MODEL_SOURCE=modelscope
```
For more information about model source configuration and custom local model paths, please refer to the [Model Source Documentation](./model_source.md) in the documentation.
--- ## Table of Contents
## Quick Usage via Command Line - [Quick Usage](./quick_usage.md) - Quick setup and basic usage
MinerU has built-in command line tools that allow users to quickly use MinerU for PDF parsing through the command line: - [Model Source Configuration](./model_source.md) - Detailed configuration instructions for model sources
```bash - [Command Line Tools](./cli_tools.md) - Detailed parameter descriptions for command line tools
# Default parsing using pipeline backend - [Advanced Optimization Parameters](./advanced_cli_parameters.md) - Advanced parameter descriptions for command line tool adaptation
mineru -p <input_path> -o <output_path>
```
> [!TIP]
>- `<input_path>`: Local PDF/image file or directory
>- `<output_path>`: Output directory
>
> For more information about output files, please refer to [Output File Documentation](../output_files.md).
> [!NOTE] ## Getting Started
> The command line tool will automatically attempt cuda/mps acceleration on Linux and macOS systems.
> Windows users who need cuda acceleration should visit the [PyTorch official website](https://pytorch.org/get-started/locally/) to select the appropriate command for their cuda version to install acceleration-enabled `torch` and `torchvision`.
We recommend reading the documentation in the order listed above, which will help you better understand and use the project features.
```bash If you encounter issues during usage, please check the [FAQ](../faq/index.md)
# Or specify vlm backend for parsing \ No newline at end of file
mineru -p <input_path> -o <output_path> -b vlm-transformers
```
> [!TIP]
> The vlm backend additionally supports `sglang` acceleration. Compared to the `transformers` backend, `sglang` can achieve 20-30x speedup. You can check the installation method for the complete package supporting `sglang` acceleration in the [Extension Modules Installation Guide](../quick_start/extension_modules.md).
If you need to adjust parsing options through custom parameters, you can also check the more detailed [Command Line Tools Usage Instructions](./cli_tools.md) in the documentation.
---
## Advanced Usage via API, WebUI, sglang-client/server
- Direct Python API calls: [Python Usage Example](https://github.com/opendatalab/MinerU/blob/master/demo/demo.py)
- FastAPI calls:
```bash
mineru-api --host 127.0.0.1 --port 8000
```
>[!TIP]
>Access `http://127.0.0.1:8000/docs` in your browser to view the API documentation.
- Start Gradio WebUI visual frontend:
```bash
# Using pipeline/vlm-transformers/vlm-sglang-client backends
mineru-gradio --server-name 127.0.0.1 --server-port 7860
# Or using vlm-sglang-engine/pipeline backends (requires sglang environment)
mineru-gradio --server-name 127.0.0.1 --server-port 7860 --enable-sglang-engine true
```
>[!TIP]
>
>- Access `http://127.0.0.1:7860` in your browser to use the Gradio WebUI.
>- Access `http://127.0.0.1:7860/?view=api` to use the Gradio API.
- Using `sglang-client/server` method:
```bash
# Start sglang server (requires sglang environment)
mineru-sglang-server --port 30000
```
>[!TIP]
>In another terminal, connect to sglang server via sglang client (only requires CPU and network, no sglang environment needed)
> ```bash
> mineru -p <input_path> -o <output_path> -b vlm-sglang-client -u http://127.0.0.1:30000
> ```
> [!TIP]
> All officially supported sglang parameters can be passed to MinerU through command line arguments, including the following commands: `mineru`, `mineru-sglang-server`, `mineru-gradio`, `mineru-api`.
> We have compiled some commonly used parameters and usage methods for `sglang`, which can be found in the documentation [Advanced Command Line Parameters](./advanced_cli_parameters.md).
---
## Extending MinerU Functionality with Configuration Files
MinerU is now ready to use out of the box, but also supports extending functionality through configuration files. You can edit `mineru.json` file in your user directory to add custom configurations.
>[!TIP]
>The `mineru.json` file will be automatically generated when you use the built-in model download command `mineru-models-download`, or you can create it by copying the [configuration template file](https://github.com/opendatalab/MinerU/blob/master/mineru.template.json) to your user directory and renaming it to `mineru.json`.
Here are some available configuration options:
- `latex-delimiter-config`: Used to configure LaTeX formula delimiters, defaults to `$` symbol, can be modified to other symbols or strings as needed.
- `llm-aided-config`: Used to configure parameters for LLM-assisted title hierarchy, compatible with all LLM models supporting `openai protocol`, defaults to using Alibaba Cloud Bailian's `qwen2.5-32b-instruct` model. You need to configure your own API key and set `enable` to `true` to enable this feature.
- `models-dir`: Used to specify local model storage directory, please specify model directories for `pipeline` and `vlm` backends separately. After specifying the directory, you can use local models by configuring the environment variable `export MINERU_MODEL_SOURCE=local`.
docs/en/usage/model_source.md
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...@@ -36,7 +36,7 @@ or use the interactive command line tool to select model downloads: ...@@ -36,7 +36,7 @@ or use the interactive command line tool to select model downloads:
```bash ```bash
mineru-models-download mineru-models-download
``` ```
>[!TIP] > [!NOTE]
>- After download completion, the model path will be output in the current terminal window and automatically written to `mineru.json` in the user directory. >- After download completion, the model path will be output in the current terminal window and automatically written to `mineru.json` in the user directory.
>- You can also create it by copying the [configuration template file](https://github.com/opendatalab/MinerU/blob/master/mineru.template.json) to your user directory and renaming it to `mineru.json`. >- You can also create it by copying the [configuration template file](https://github.com/opendatalab/MinerU/blob/master/mineru.template.json) to your user directory and renaming it to `mineru.json`.
>- After downloading models locally, you can freely move the model folder to other locations while updating the model path in `mineru.json`. >- After downloading models locally, you can freely move the model folder to other locations while updating the model path in `mineru.json`.
......
docs/en/usage/quick_usage.md 0 → 100644
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# Using MinerU
## Quick Model Source Configuration
MinerU uses `huggingface` as the default model source. If users cannot access `huggingface` due to network restrictions, they can conveniently switch the model source to `modelscope` through environment variables:
```bash
export MINERU_MODEL_SOURCE=modelscope
```
For more information about model source configuration and custom local model paths, please refer to the [Model Source Documentation](./model_source.md) in the documentation.
---
## Quick Usage via Command Line
MinerU has built-in command line tools that allow users to quickly use MinerU for PDF parsing through the command line:
```bash
# Default parsing using pipeline backend
mineru -p <input_path> -o <output_path>
```
> [!TIP]
>- `<input_path>`: Local PDF/image file or directory
>- `<output_path>`: Output directory
>
> For more information about output files, please refer to [Output File Documentation](../reference/output_files.md).
> [!NOTE]
> The command line tool will automatically attempt cuda/mps acceleration on Linux and macOS systems.
> Windows users who need cuda acceleration should visit the [PyTorch official website](https://pytorch.org/get-started/locally/) to select the appropriate command for their cuda version to install acceleration-enabled `torch` and `torchvision`.
```bash
# Or specify vlm backend for parsing
mineru -p <input_path> -o <output_path> -b vlm-transformers
```
> [!TIP]
> The vlm backend additionally supports `sglang` acceleration. Compared to the `transformers` backend, `sglang` can achieve 20-30x speedup. You can check the installation method for the complete package supporting `sglang` acceleration in the [Extension Modules Installation Guide](../quick_start/extension_modules.md).
If you need to adjust parsing options through custom parameters, you can also check the more detailed [Command Line Tools Usage Instructions](./cli_tools.md) in the documentation.
---
## Advanced Usage via API, WebUI, sglang-client/server
- Direct Python API calls: [Python Usage Example](https://github.com/opendatalab/MinerU/blob/master/demo/demo.py)
- FastAPI calls:
```bash
mineru-api --host 127.0.0.1 --port 8000
```
>[!TIP]
>Access `http://127.0.0.1:8000/docs` in your browser to view the API documentation.
- Start Gradio WebUI visual frontend:
```bash
# Using pipeline/vlm-transformers/vlm-sglang-client backends
mineru-gradio --server-name 127.0.0.1 --server-port 7860
# Or using vlm-sglang-engine/pipeline backends (requires sglang environment)
mineru-gradio --server-name 127.0.0.1 --server-port 7860 --enable-sglang-engine true
```
>[!TIP]
>
>- Access `http://127.0.0.1:7860` in your browser to use the Gradio WebUI.
>- Access `http://127.0.0.1:7860/?view=api` to use the Gradio API.
- Using `sglang-client/server` method:
```bash
# Start sglang server (requires sglang environment)
mineru-sglang-server --port 30000
```
>[!TIP]
>In another terminal, connect to sglang server via sglang client (only requires CPU and network, no sglang environment needed)
> ```bash
> mineru -p <input_path> -o <output_path> -b vlm-sglang-client -u http://127.0.0.1:30000
> ```
> [!NOTE]
> All officially supported sglang parameters can be passed to MinerU through command line arguments, including the following commands: `mineru`, `mineru-sglang-server`, `mineru-gradio`, `mineru-api`.
> We have compiled some commonly used parameters and usage methods for `sglang`, which can be found in the documentation [Advanced Command Line Parameters](./advanced_cli_parameters.md).
---
## Extending MinerU Functionality with Configuration Files
MinerU is now ready to use out of the box, but also supports extending functionality through configuration files. You can edit `mineru.json` file in your user directory to add custom configurations.
>[!IMPORTANT]
>The `mineru.json` file will be automatically generated when you use the built-in model download command `mineru-models-download`, or you can create it by copying the [configuration template file](https://github.com/opendatalab/MinerU/blob/master/mineru.template.json) to your user directory and renaming it to `mineru.json`.
Here are some available configuration options:
- `latex-delimiter-config`: Used to configure LaTeX formula delimiters, defaults to `$` symbol, can be modified to other symbols or strings as needed.
- `llm-aided-config`: Used to configure parameters for LLM-assisted title hierarchy, compatible with all LLM models supporting `openai protocol`, defaults to using Alibaba Cloud Bailian's `qwen2.5-32b-instruct` model. You need to configure your own API key and set `enable` to `true` to enable this feature.
- `models-dir`: Used to specify local model storage directory, please specify model directories for `pipeline` and `vlm` backends separately. After specifying the directory, you can use local models by configuring the environment variable `export MINERU_MODEL_SOURCE=local`.
docs/zh/quick_start/index.md
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...@@ -93,4 +93,9 @@ MinerU提供了便捷的docker部署方式，这有助于快速搭建环境并 ...@@ -93,4 +93,9 @@ MinerU提供了便捷的docker部署方式，这有助于快速搭建环境并
### 使用 MinerU ### 使用 MinerU
最简单的命令行调用方式:
```bash
mineru -p <input_path> -o <output_path>
```
您可以通过命令行、API、WebUI等多种方式使用MinerU进行PDF解析，具体使用方法请参考[使用指南](../usage/index.md)。 您可以通过命令行、API、WebUI等多种方式使用MinerU进行PDF解析，具体使用方法请参考[使用指南](../usage/index.md)。
\ No newline at end of file
docs/zh/usage/advanced_cli_parameters.md
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# 命令行参数进阶技巧 # 命令行参数进阶
--- ---
......
docs/zh/usage/index.md
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# 使用 MinerU # 使用指南
## 快速配置模型源 本章节提供了项目的完整使用说明。我们将通过以下几个部分，帮助您从基础到进阶逐步掌握项目的使用方法：
MinerU默认使用`huggingface`作为模型源，若用户网络无法访问`huggingface`，可以通过环境变量便捷地切换模型源为`modelscope`：
```bash
export MINERU_MODEL_SOURCE=modelscope
```
有关模型源配置和自定义本地模型路径的更多信息，请参考文档中的[模型源说明](./model_source.md)。
--- ## 目录
## 通过命令行快速使用 - [快速使用](./quick_usage.md) - 快速上手和基本使用
MinerU内置了命令行工具，用户可以通过命令行快速使用MinerU进行PDF解析： - [模型源配置](./model_source.md) - 模型源的详细配置说明
```bash - [命令行工具](./cli_tools.md) - 命令行工具的详细参数说明
# 默认使用pipeline后端解析 - [进阶优化参数](./advanced_cli_parameters.md) - 一些适配命令行工具的进阶参数说明
mineru -p <input_path> -o <output_path>
```
> [!TIP]
> - `<input_path>`：本地 PDF/图片 文件或目录
> - `<output_path>`：输出目录
>
> 更多关于输出文件的信息，请参考[输出文件说明](../output_files.md)。
> [!NOTE] ## 开始使用
> 命令行工具会在Linux和macOS系统自动尝试cuda/mps加速。Windows用户如需使用cuda加速，
> 请前往 [Pytorch官网](https://pytorch.org/get-started/locally/) 选择适合自己cuda版本的命令安装支持加速的`torch`和`torchvision`。
建议按照上述顺序阅读文档，这样可以帮助您更好地理解和使用项目功能。
```bash 如果您在使用过程中遇到问题，请查看 [FAQ](../faq/index.md)
# 或指定vlm后端解析 \ No newline at end of file
mineru -p <input_path> -o <output_path> -b vlm-transformers
```
> [!TIP]
> vlm后端另外支持`sglang`加速，与`transformers`后端相比，`sglang`的加速比可达20～30倍，可以在[扩展模块安装指南](../quick_start/extension_modules.md)中查看支持`sglang`加速的完整包安装方法。
如果需要通过自定义参数调整解析选项，您也可以在文档中查看更详细的[命令行工具使用说明](./cli_tools.md)。
---
## 通过api、webui、sglang-client/server进阶使用
- 通过python api直接调用：[Python 调用示例](https://github.com/opendatalab/MinerU/blob/master/demo/demo.py)
- 通过fast api方式调用：
```bash
mineru-api --host 127.0.0.1 --port 8000
```
>[!TIP]
>在浏览器中访问 `http://127.0.0.1:8000/docs` 查看API文档。
- 启动gradio webui 可视化前端：
```bash
# 使用 pipeline/vlm-transformers/vlm-sglang-client 后端
mineru-gradio --server-name 127.0.0.1 --server-port 7860
# 或使用 vlm-sglang-engine/pipeline 后端（需安装sglang环境）
mineru-gradio --server-name 127.0.0.1 --server-port 7860 --enable-sglang-engine true
```
>[!TIP]
>
>- 在浏览器中访问 `http://127.0.0.1:7860` 使用 Gradio WebUI。
>- 访问 `http://127.0.0.1:7860/?view=api` 使用 Gradio API。
- 使用`sglang-client/server`方式调用：
```bash
# 启动sglang server(需要安装sglang环境)
mineru-sglang-server --port 30000
```
>[!TIP]
>在另一个终端中通过sglang client连接sglang server（只需cpu与网络，不需要sglang环境）
> ```bash
> mineru -p <input_path> -o <output_path> -b vlm-sglang-client -u http://127.0.0.1:30000
> ```
> [!TIP]
> 所有sglang官方支持的参数都可用通过命令行参数传递给 MinerU，包括以下命令:`mineru`、`mineru-sglang-server`、`mineru-gradio`、`mineru-api`，
> 我们整理了一些`sglang`使用中的常用参数和使用方法，可以在文档[命令行进阶参数](./advanced_cli_parameters.md)中获取。
---
## 基于配置文件扩展 MinerU 功能
MinerU 现已实现开箱即用，但也支持通过配置文件扩展功能。您可通过编辑用户目录下的 `mineru.json` 文件，添加自定义配置。
>[!TIP]
>`mineru.json` 文件会在您使用内置模型下载命令 `mineru-models-download` 时自动生成，也可以通过将[配置模板文件](https://github.com/opendatalab/MinerU/blob/master/mineru.template.json)复制到用户目录下并重命名为 `mineru.json` 来创建。
以下是一些可用的配置选项：
- `latex-delimiter-config`：用于配置 LaTeX 公式的分隔符，默认为`$`符号，可根据需要修改为其他符号或字符串。
- `llm-aided-config`：用于配置 LLM 辅助标题分级的相关参数，兼容所有支持`openai协议`的 LLM 模型，默认使用`阿里云百炼`的`qwen2.5-32b-instruct`模型，您需要自行配置 API 密钥并将`enable`设置为`true`来启用此功能。
- `models-dir`：用于指定本地模型存储目录，请为`pipeline`和`vlm`后端分别指定模型目录，指定目录后您可通过配置环境变量`export MINERU_MODEL_SOURCE=local`来使用本地模型。
docs/zh/usage/model_source.md
View file @ 0775d4dc
...@@ -37,7 +37,7 @@ mineru-models-download --help ...@@ -37,7 +37,7 @@ mineru-models-download --help
```bash ```bash
mineru-models-download mineru-models-download
``` ```
>[!TIP] > [!NOTE]
>- 下载完成后，模型路径会在当前终端窗口输出，并自动写入用户目录下的 `mineru.json`。 >- 下载完成后，模型路径会在当前终端窗口输出，并自动写入用户目录下的 `mineru.json`。
>- 您也可以通过将[配置模板文件](https://github.com/opendatalab/MinerU/blob/master/mineru.template.json)复制到用户目录下并重命名为 `mineru.json` 来创建配置文件。 >- 您也可以通过将[配置模板文件](https://github.com/opendatalab/MinerU/blob/master/mineru.template.json)复制到用户目录下并重命名为 `mineru.json` 来创建配置文件。
>- 模型下载到本地后，您可以自由移动模型文件夹到其他位置，同时需要在 `mineru.json` 中更新模型路径。 >- 模型下载到本地后，您可以自由移动模型文件夹到其他位置，同时需要在 `mineru.json` 中更新模型路径。
......
docs/zh/usage/quick_usage.md 0 → 100644
View file @ 0775d4dc
# 使用 MinerU
## 快速配置模型源
MinerU默认使用`huggingface`作为模型源，若用户网络无法访问`huggingface`，可以通过环境变量便捷地切换模型源为`modelscope`：
```bash
export MINERU_MODEL_SOURCE=modelscope
```
有关模型源配置和自定义本地模型路径的更多信息，请参考文档中的[模型源说明](./model_source.md)。
---
## 通过命令行快速使用
MinerU内置了命令行工具，用户可以通过命令行快速使用MinerU进行PDF解析：
```bash
# 默认使用pipeline后端解析
mineru -p <input_path> -o <output_path>
```
> [!TIP]
> - `<input_path>`：本地 PDF/图片 文件或目录
> - `<output_path>`：输出目录
>
> 更多关于输出文件的信息，请参考[输出文件说明](../reference/output_files.md)。
> [!NOTE]
> 命令行工具会在Linux和macOS系统自动尝试cuda/mps加速。Windows用户如需使用cuda加速，
> 请前往 [Pytorch官网](https://pytorch.org/get-started/locally/) 选择适合自己cuda版本的命令安装支持加速的`torch`和`torchvision`。
```bash
# 或指定vlm后端解析
mineru -p <input_path> -o <output_path> -b vlm-transformers
```
> [!TIP]
> vlm后端另外支持`sglang`加速，与`transformers`后端相比，`sglang`的加速比可达20～30倍，可以在[扩展模块安装指南](../quick_start/extension_modules.md)中查看支持`sglang`加速的完整包安装方法。
如果需要通过自定义参数调整解析选项，您也可以在文档中查看更详细的[命令行工具使用说明](./cli_tools.md)。
---
## 通过api、webui、sglang-client/server进阶使用
- 通过python api直接调用：[Python 调用示例](https://github.com/opendatalab/MinerU/blob/master/demo/demo.py)
- 通过fast api方式调用：
```bash
mineru-api --host 127.0.0.1 --port 8000
```
>[!TIP]
>在浏览器中访问 `http://127.0.0.1:8000/docs` 查看API文档。
- 启动gradio webui 可视化前端：
```bash
# 使用 pipeline/vlm-transformers/vlm-sglang-client 后端
mineru-gradio --server-name 127.0.0.1 --server-port 7860
# 或使用 vlm-sglang-engine/pipeline 后端（需安装sglang环境）
mineru-gradio --server-name 127.0.0.1 --server-port 7860 --enable-sglang-engine true
```
>[!TIP]
>
>- 在浏览器中访问 `http://127.0.0.1:7860` 使用 Gradio WebUI。
>- 访问 `http://127.0.0.1:7860/?view=api` 使用 Gradio API。
- 使用`sglang-client/server`方式调用：
```bash
# 启动sglang server(需要安装sglang环境)
mineru-sglang-server --port 30000
```
>[!TIP]
>在另一个终端中通过sglang client连接sglang server（只需cpu与网络，不需要sglang环境）
> ```bash
> mineru -p <input_path> -o <output_path> -b vlm-sglang-client -u http://127.0.0.1:30000
> ```
> [!NOTE]
> 所有sglang官方支持的参数都可用通过命令行参数传递给 MinerU，包括以下命令:`mineru`、`mineru-sglang-server`、`mineru-gradio`、`mineru-api`，
> 我们整理了一些`sglang`使用中的常用参数和使用方法，可以在文档[命令行进阶参数](./advanced_cli_parameters.md)中获取。
---
## 基于配置文件扩展 MinerU 功能
MinerU 现已实现开箱即用，但也支持通过配置文件扩展功能。您可通过编辑用户目录下的 `mineru.json` 文件，添加自定义配置。
>[!IMPORTANT]
>`mineru.json` 文件会在您使用内置模型下载命令 `mineru-models-download` 时自动生成，也可以通过将[配置模板文件](https://github.com/opendatalab/MinerU/blob/master/mineru.template.json)复制到用户目录下并重命名为 `mineru.json` 来创建。
以下是一些可用的配置选项：
- `latex-delimiter-config`：用于配置 LaTeX 公式的分隔符，默认为`$`符号，可根据需要修改为其他符号或字符串。
- `llm-aided-config`：用于配置 LLM 辅助标题分级的相关参数，兼容所有支持`openai协议`的 LLM 模型，默认使用`阿里云百炼`的`qwen2.5-32b-instruct`模型，您需要自行配置 API 密钥并将`enable`设置为`true`来启用此功能。
- `models-dir`：用于指定本地模型存储目录，请为`pipeline`和`vlm`后端分别指定模型目录，指定目录后您可通过配置环境变量`export MINERU_MODEL_SOURCE=local`来使用本地模型。
mkdocs.yml
View file @ 0775d4dc
...@@ -56,12 +56,12 @@ extra: ...@@ -56,12 +56,12 @@ extra:
name: GitHub name: GitHub
- icon: fontawesome/brands/x-twitter - icon: fontawesome/brands/x-twitter
link: https://x.com/OpenDataLab_AI link: https://x.com/OpenDataLab_AI
name: Twitter name: X-Twitter
- icon: fontawesome/brands/discord - icon: fontawesome/brands/discord
link: https://discord.gg/Tdedn9GTXq link: https://discord.gg/Tdedn9GTXq
name: Discord name: Discord
- icon: fontawesome/brands/weixin - icon: fontawesome/brands/weixin
link: https://mineru.space/common/qun/?qid=362634 link: http://mineru.space/s/V85Yl
name: WeChat name: WeChat
- icon: material/email - icon: material/email
link: mailto:OpenDataLab@pjlab.org.cn link: mailto:OpenDataLab@pjlab.org.cn
......
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